1 / 25

EKF and UKF

Day 24. EKF and UKF. EKF and RoboCup Soccer. simulation of localization using EKF and 6 landmarks (with known correspondences) robot travels in a circular arc of length 90cm and rotation 45deg. EKF Prediction Step.

sanaa
Download Presentation

EKF and UKF

An Image/Link below is provided (as is) to download presentation Download Policy: Content on the Website is provided to you AS IS for your information and personal use and may not be sold / licensed / shared on other websites without getting consent from its author. Content is provided to you AS IS for your information and personal use only. Download presentation by click this link. While downloading, if for some reason you are not able to download a presentation, the publisher may have deleted the file from their server. During download, if you can't get a presentation, the file might be deleted by the publisher.

E N D

Presentation Transcript


  1. Day 24 EKF and UKF

  2. EKF and RoboCup Soccer • simulation of localization using EKF and 6 landmarks (with known correspondences) • robot travels in a circular arc of length 90cm and rotation 45deg

  3. EKF Prediction Step • recall that in the prediction step the state mean and covariance are projected forward in time using the plant model

  4. EKF Prediction Step position and covariance at previous time step

  5. EKF Prediction Step uncertainty due to control noise (small transl. and rot. noise)

  6. EKF Prediction Step previous uncertainty projected through process model

  7. EKF Prediction Step net predicted uncertainty

  8. EKF Prediction Step uncertainty due to control noise (large transl. and small rot. noise)

  9. EKF Prediction Step uncertainty due to control noise (small transl. and large rot. noise)

  10. EKF Prediction Step uncertainty due to control noise (large transl. and large rot. noise)

  11. EKF Observation Prediction Step • in the first part of the correction step, the measurement model is used to predict the measurement and its covariance using the predicted state and its covariance

  12. EKF Observation Prediction Step predicted state with covariance predicted landmark observation landmark observation

  13. EKF Observation Prediction Step predicted state with uncertainty observation uncertainty landmark observation

  14. EKF Observation Prediction Step uncertainty due to uncertainty in predicted robotposition predicted state with covariance landmark observation

  15. EKF Observation Prediction Step innovation (difference between predicted and actual observations) predicted state with covariance landmark observation

  16. EKF Observation Prediction Step predicted state with uncertainty observation uncertainty (large distance uncertainty) landmark observation

  17. EKF Observation Prediction Step predicted state with uncertainty observation uncertainty (large bearing uncertainty) landmark observation

  18. EKF Correction Step • the correction step updates the state estimate using the innovation vector and the measurement prediction uncertainty

  19. EKF Correction Step innovation (difference between predicted and actual observations) innovation scaled and mapped into state space

  20. EKF Correction Step corrected state mean corrected state uncertainty

  21. EKF Correction Step

  22. Estimation Sequence (1) EKF estimated path initial position uncertainty true path landmark measurement event predicted position uncertainty corrected position uncertainty motion model estimated path

  23. Estimation Sequence (2) same as previous but with greater measurement uncertainty

  24. Comparison to GroundTruth

  25. EKF Summary • Highly efficient: Polynomial in measurement dimensionality k and state dimensionality n: O(k2.376 + n2) • Not optimal! • Can diverge if nonlinearities are large! • Works surprisingly well even when all assumptions are violated!

More Related